Analysis Of Skin Lesions Using Gmm-Hmrf Region-Based Segmentation Technique (Applied Biological Research, 2019)
This paper was aimed to develop a computer-aided detection (CAD) system  which may support dermatologists in their early diagnosis of skin cancer from dermoscopic images. Segmentation play key role in the automatic  detection of skin lesions. In this paper Gaussian Mixture Model-based  Hidden Markov Random Field (GMM-HMRF) region-based segmentation  method was used. The technique is fast and automated for dermoscopic  images and is used in quantitative experimental analysis for publicly  available data base and compared with two other well-known methods. The  results revealed that the proposed method was highly accurate. The proposed  segmentation technique achieved remarkable results for nevus images [accuracy (ACC) = 97.21%, sensitivity (SE) = 95.43% and specificity (SP) = 91.76%]; while for benign images (ACC = 96.15%, SE = 96.26% and SP = 95.32) and basal cell carcinoma & Seborrheic keratoses images (ACC = 96.85%, SE = 96.85% and SP = 97.34) the results were almost same.
Keywords: Feature extraction; fuzzy C-mean; GMM-HMRF; segmentation